{"id":"W2890353242","doi":"10.23889/ijpds.v3i4.969","title":"Developing and implementing linked electronic medical record and administrative data in primary care practice for diabetes in Alberta","year":2018,"lang":"en","type":"article","venue":"International Journal for Population Data Science","topic":"Diabetes Management and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Alberta Health Services; Alberta Innovates; University of Calgary; University of Alberta","funders":"","keywords":"Medicine; Medical record; Dashboard; Family medicine; Diabetes mellitus; Primary care; Health care; Medical emergency; Database; Internal medicine","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.02206698,0.0003042627,0.0002448124,0.003361029,0.002589038,0.004284087,0.003283579,0.0006282146,0.001847249],"category_scores_gemma":[0.03534437,0.0005296607,0.0005534202,0.005083246,0.001098591,0.001063477,0.003920522,0.0007662446,0.0003636953],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.05071607,"about_ca_system_score_gemma":0.1030616,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9556374,"about_ca_topic_score_gemma":0.954233,"domain_scores_codex":[0.9846549,0.004299823,0.001092978,0.001140588,0.006566754,0.002245023],"domain_scores_gemma":[0.968093,0.00880599,0.002527764,0.002253181,0.01403571,0.004284368],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0006643328,0.000883878,0.6772293,0.0006799978,0.0001765805,0.000578013,0.01083137,0.00681452,0.002792815,0.002653773,0.01229991,0.2843955],"study_design_scores_gemma":[0.0004502324,0.0008691021,0.9222559,0.0006573159,0.0001828628,0.0001757382,0.01633801,0.02112904,0.002896427,0.0008093926,0.03412731,0.0001087278],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9354208,0.00136982,0.01292156,0.009552625,0.0001661854,0.006939053,0.01198653,0.001408261,0.02023529],"genre_scores_gemma":[0.8982182,0.0009618101,0.08570148,0.001729935,0.00007977862,0.001673749,0.007819017,0.0000821478,0.003733919],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05071607,"threshold_uncertainty_score":0.3679726,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.09774433257932558,"score_gpt":0.4586427995717345,"score_spread":0.3608984669924089,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}